APPLICATION OF EVOLVED EVOLUTIONARY ALGORITHMS FOR THE SOLUTION OF DIFFERENT ASPECTS OF HYDROTHERMAL SCHEDULING – A COMPREHENSIVE OVERVIEW
Abstract
Hydrothermal Scheduling (HTS) presents highly complicated, non-linear and multi-constrained optimization problem. Usually very turbulent and non-convex search space is linked with Hydrothermal (HT) Scheduling problem. So rather a robust and powerful optimization tool is required to optimize this problem efficiently. In literature, so far, many powerful and robust optimization algorithms have been employed for the solution of HTS problem. Genetic Algorithm (GA) represents one of the most established while Bacterial Foraging Algorithm (BFA) represents one of the newest Evolutionary Algorithms. Both GA and BFA are being actively deployed to solve non convex optimization problems, where conventional approaches have rather failed to provide acceptable results. The aim of this research paper is to provide a comprehensive survey of literature related to both GA and BFA as effective optimization algorithms for the solution of various aspects of HTS problem. The outcomes alongwith both strengths and weaknesses of individual algorithms are also discussed.References
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